Documentation Index
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Solana trading pools and their daily volume.
dimensions.dex_pools: one row per pool.metrics_dex_pools: one table per measure, one row per pool per day.metrics_dex_pool_pairs: one row per pool and traded token pair per day, in trading_volume_daily.timestamp and filter chain_id in every query; without them the query reads the whole table.with top_pools as (
select
dex_pool_id,
trading_volume
from `metrics_dex_pools.trading_volume_daily`
where timestamp >= timestamp('2026-08-20')
and timestamp < timestamp('2026-08-21')
and chain_id = 'solana'
order by trading_volume desc
limit 20
)
select
pools.pool_display_name,
pools.protocol_id as app_id,
top_pools.trading_volume
from top_pools
join `dimensions.dex_pools` as pools
using (dex_pool_id)
order by top_pools.trading_volume desc
dimensions.dex_pools names the app under the older name protocol_id, so the query aliases it; the pool grain is the only place the split exists, since one venue’s pools number in the millions.with day_volume as (
select
dex_pool_id,
trading_volume
from `metrics_dex_pools.trading_volume_daily`
where timestamp >= timestamp('2026-08-20')
and timestamp < timestamp('2026-08-21')
and chain_id = 'solana'
)
select
pools.protocol_id as app_id,
count(*) as pools_traded,
sum(day_volume.trading_volume) as trading_volume
from day_volume
join `dimensions.dex_pools` as pools
using (dex_pool_id)
group by app_id
order by trading_volume desc
dex_pair_id joins the two mint addresses and the chain in sorted address order, so the same two tokens produce the same identifier whichever way round the trade went.select
dex_pair_id,
count(distinct dex_pool_id) as pools,
sum(trading_volume) as trading_volume
from `metrics_dex_pool_pairs.trading_volume_daily`
where timestamp >= timestamp('2026-08-16')
and timestamp < timestamp('2026-08-23')
and chain_id = 'solana'
group by dex_pair_id
order by trading_volume desc
limit 20